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Summary: This paper presents the development of a single‐phase voltage source inverter (VSI) of 3.5KW, applied to grid‐connected photovoltaic systems (GCPS). The proposed system has a boost interface converter connected to a full bridge inverter with an LCL filter. Each block that constitutes the proposed GCPS is described in detail, containing the specifications of the solar modules, the design of the power circuit components, the mathematical modeling, and the control design of the converters. The presentation of the Volt‐VAR Control (VVC) highlights the contribution of this work, where it is implemented with the intention of the inverter to supply/consume reactive power, in order to minimize voltage variations at the point of common coupling (PCC). To validate the inverter operation with VVC, three cases are presented, encompassing grid voltage and irradiance variations, and load steps. Through the PCC voltage profiles, currents, and power supplied/consumed, the means to demonstrate the effectiveness of the proposed control is shown. The results obtained through the PSIM simulations and verified by Typhoon Hardware in the Loop (HIL) model, showed the regulation of grid voltage levels for all established conditions. [ABSTRACT FROM AUTHOR]

The mining industry is a key contributor to Western Australia's economy, with over 130 mining operations that produce critical minerals such as iron ore, gold, and lithium. Ensuring a reliable and continuous energy supply is vital for these operations. This paper addresses the challenges and opportunities of integrating renewable energy sources into isolated power systems, particularly under uncertainties associated with renewable energy generation and demand. A robust optimization approach is developed to model a multi-source hybrid energy system that considers risk-averse, risk-neutral, and risk-seeking strategies. These strategies address power demand and renewable energy supply uncertainties, ensuring system reliability under various risk scenarios. The optimization framework, formulated as a mixed integer linear programming problem and implemented in Python using the Gurobi Optimizer, integrates renewable energy sources such as wind turbines, photovoltaic arrays, and demand response programs alongside traditional diesel generators, boilers, combined heat and power units, and water desalination. The model ensures reliable access to electricity, heat, and water while minimizing operational costs and reducing reliance on fossil fuels. A comprehensive sensitivity analysis further examines the impact of uncertainty margins and the value of a lost load on the total system cost, providing insights into how different risk strategies affect system performance and cost-efficiency. The results are validated through three case studies demonstrating the effectiveness of the proposed approach in enhancing the resilience and sustainability of isolated power systems in the mining sector. Significant improvements in reliability, scalability, and economic performance are observed, with the sensitivity analysis highlighting the critical trade-offs between cost and reliability under varying uncertainty conditions. [ABSTRACT FROM AUTHOR]

The growing demand for alternative energy sources to alleviate environmental impacts highlights the need to move from fossil fuels to renewable energy. This study demonstrated the technical feasibility of using a solar photovoltaic (PV) system for the production of green hydrogen. This research examined electrical and power data from a PV plant in Irecê, Bahia, using open data sources to provide insights into the production of green hydrogen from renewable sources. The system mainly depends on the use of a renewable source, PV solar energy, integrated with batteries, electrolyzers, and hydrogen tanks. Electrolyzer, battery, and hydrogen tank sizing analysis for optimal hydrogen production was effectively conducted using HOMER Energy software. The predicted system topology prioritizes a local DC network, optimizing efficiency for electrolyzers that have inherently low efficiency. The electrolyzer simulation involves initial Python‐based sizing and comprehensive sizing with HOMER Energy software, ensuring accuracy within a 10% discrepancy limit. This highlights the importance of analytical calculations and optimization software for sizing more complex systems. [ABSTRACT FROM AUTHOR]

The circular economy (CE) strategies in energy communities enable firms to efficiently manage the excess of photovoltaic energy they produce, and thereby enhance their sustainability. Thus, the present research aims to compare the economic and financial profitability and greenhouse gas (GHG) emissions of shared photovoltaic self‐consumption versus individual self‐consumption in the region of Extremadura (Spain). Six firms with complementary energy profiles were selected, analyzing their hourly energy consumption. In addition, the Monte Carlo method was used to generate 30,000 simulations, reducing the uncertainty caused by the variability of the firms' energy consumption. The results show that collective generation covers the energy needs more efficiently, reducing the cost of energy consumed by 14.38% and generating better cost–benefit ratio. They also show that the CE strategy of the energy community allows firms to obtain a considerable reduction of GHG emissions associated with the photovoltaic energy consumed. [ABSTRACT FROM AUTHOR]

Abstract The growing demand for alternative energy sources to alleviate environmental impacts highlights the need to move from fossil fuels to renewable energy. This study demonstrated the technical feasibility of using a solar photovoltaic (PV) system for the production of green hydrogen. This research examined electrical and power data from a PV plant in Irecê, Bahia, using open data sources to provide insights into the production of green hydrogen from renewable sources. The system mainly depends on the use of a renewable source, PV solar energy, integrated with batteries, electrolyzers, and hydrogen tanks. Electrolyzer, battery, and hydrogen tank sizing analysis for optimal hydrogen production was effectively conducted using HOMER Energy software. The predicted system topology prioritizes a local DC network, optimizing efficiency for electrolyzers that have inherently low efficiency. The electrolyzer simulation involves initial Python‐based sizing and comprehensive sizing with HOMER Energy software, ensuring accuracy within a 10% discrepancy limit. This highlights the importance of analytical calculations and optimization software for sizing more complex systems.

In the field of renewable energies, the logistical intricacies of production, as well as the use and storage of photovoltaic energy, have become critical issues. In addition to sheer quantity, the stability of this type of energy is a crucial factor in ensuring the reliability and consistency of power generation. This paper defines Solar Irradiance Stability Factors (SISFs) as indicators complementing electricity production. When planning solar energy production in each geographical area, both the quantity and stability of solar irradiance are necessary for exploitation and determining the quality of solar irradiance. While the average production of solar energy per unit area in each time interval is a widely used parameter in daily practice, the observation of the amplitude of solar irradiance and its influence on energy production in the observed time interval is currently still rare. The SISFs defined in this article are new metrics that mainly depend on the meteorological variability in an area, and the observed time intervals should be in the range of seconds, minutes, or even hours. Larger time intervals are not helpful for the stability of solar irradiance in energy production and logistics from the source to the destination. They provide a complementary and more accurate measure of how suitable a particular geographical area is for producing solar energy. [ABSTRACT FROM AUTHOR]

The global photovoltaic (PV) installed capacity, vital for the electric sector's decarbonation, reached 1552.3 GW p in 2023. In France, the capacity stood at 19.9 GW p in April 2024. The growth of the PV installed capacity over a year was nearly 32% worldwide and 15.7% in France. However, integrating PV electricity into grids is hindered by poor knowledge of rooftop PV systems, constituting 20% of France's installed capacity, and the lack of measurements of the production stemming from these systems. This problem of lack of measurements of the rooftop PV power production is referred to as the lack of observability. Using ground-truth measurements of individual PV systems, available at an unprecedented temporal and spatial scale, we show that by estimating the PV power production of an individual rooftop system by combining solar irradiance and temperature data, the characteristics of the PV system inferred from remote sensing methods and an irradiation-to-electric power conversion model provides accurate estimations of the PV power production. We report an average estimation error (measured with the pRMSE) of 10% relative to the system size. Our study shows that we can improve rooftop PV observability, and thus its integration into the electric grid, using little information on these systems, a simple model of the PV system, and weather data. More broadly, this study shows that limited information is sufficient to derive a reasonably good estimation of the PV power production of small-scale systems. [ABSTRACT FROM AUTHOR]

The significant expansion of renewable energies has led to an increased importance of storage systems. Decentralized storage solutions, including Home Battery Energy Storage Systems (HBESSs) and District Battery Energy Storage Systems (DBESSs), play a crucial role in this context. This study compares individual HBESSs with a community-used DBESS regarding the grade of autarky and self-consumption, specifically focusing on a planned residential area consisting of 36 single-family houses. A simulation tool was developed to conduct load flow simulations based on household electricity consumption, wallbox profiles for electric vehicle charging, and photovoltaic generation data across various battery capacities and system boundaries. The results demonstrate that the DBESS, compared to individual HBESSs with equivalent cumulative battery capacities, can achieve a maximum increase in the grade of autarky of up to 11.6 %, alongside an 8.0 % increase in the grade of self-consumption for the given use case. In terms of capacity, the DBESS allows for a saving of up to 68% compared to HBESS to achieve similar results for the studied neighborhood. [ABSTRACT FROM AUTHOR]

Sustainable development is a global policy that requires the collective effort of the actors present in each territory. In this sense, an energy renewal intervention model is presented at the Juan XXIII Educational Institution in the city of Monteria, Córdoba, Colombia, which results from alliances between international, national, and regional actors, becoming a reference that could serve as a basis. To be replicated in other institutions with characteristics similar to those described in this case. The model generally describes the entire process carried out in the intervention and focuses on the benefits generated for the educational community. Among the main results, the increase in thermal, lighting, and acoustic comfort of the educational community stands out, according to a survey and semi-structured interviews carried out. A fact that could be attributed to the perception of increased comfort in the community is the increase in the student population in 2022, going from 1,478 in 2019 to 1,909 in 2022, with a growth of approximately 29%. Energy renovation also resulted in the improvement of the indoor climate of the classrooms (from 35°C to 27°C), the improvement in the physical infrastructure of the institution, the integration of photovoltaic solar energy, and the subsequent reduction of energy cost. [ABSTRACT FROM AUTHOR]

The optimal sitting and operation of Battery Energy Storage Systems (BESS) plays a key role in energy transition and sustainability. This paper presents an optimization framework based on a Multi-period Optimal Power Flow (MOPF) for the optimal sitting and operation of BESS alongside PV in active distribution grids. The model was implemented in AMPL (A Mathematical Programming Language) and solved using the Knitro solver to minimize power losses over one week, divided into hourly intervals. To demonstrate the applicability of the proposed model, various analyses were conducted on a benchmark 33-bus distribution network considering 1, 2 and 3 BESS. Along with the reduction in power losses of up to 17.95%, 26% and 29%, respectively. In all cases, there was an improvement in the voltage profile and a more uniform generation curve at the substation. An additional study showed that operating over a one-week horizon results in an energy gain of 1.08 MWh per day compared to single daily operations. The findings suggest that the proposed model for optimal sitting and operation of BESS in the presence of Renewable Energy Sources (RES) applies to real-world scenarios. [ABSTRACT FROM AUTHOR]

More than two-thirds of the installed solar power in Brazil comes from distributed mini-generation and microgeneration (DMMG), mostly residential and for local self-consumption of solar PV. DMMG had its legal framework approved in 2022, gradually introduces charges for distribution network use, previously exempt. To understand these implications, this article compiles recent legislative and normative changes, particularly for solar PV DMMG projects. In addition, the present study focuses on the use of DMMG systems in the city of Fortaleza in the Northeast Region. The study includes an analysis of the integration of photovoltaic plants in homes in Fortaleza and their economic viability under the new conditions established after 2020. Two residential photovoltaic systems, with varying power levels common in the residential sector of Fortaleza, were studied. Each plant underwent three analyses: one with vested rights; another with 100% taxation of FIO Bl and a third for the current scenario, factoring in the growing FIO B charge from 15% in 2023 to 100% in 2029. Customers who obtained the system by cash payment or financing were considered. An economic feasibility study factored in a 5.79% yearly inflation rate and an 11.35% annual tariff readjustment across the two plants, including sensitivity analysis for this variable. [ABSTRACT FROM AUTHOR]

The integration of photovoltaic (PV) solar energy into the utility grid is expanding progressively to meet increasing energy demand. A crucial aspect of optimizing the output of PV systems involves implementing efficient maximum power point tracking (MPPT) controllers, necessary due to the nonlinear characteristics of these systems. This study conducts a simulation-based comparative analysis of two prominent MPPT techniques: hill climbing (HC) and incremental conductance (INC) methods. The emphasis is on the dynamic response and steady-state efficiency of these controllers. Using a modeled 500 kW PV array alongside both MPPT techniques and other DC stage components, simulation tests were conducted in Matlab/Simulink under standard test conditions (STC) and varying meteorological conditions. The simulation results indicate that both techniques successfully tracked the MPP. However, the INC algorithm exhibits superior speed, precision, and efficiency, particularly in scenarios involving sudden fluctuations in irradiance and temperature. Furthermore, investigating the effect of perturbation step size on dynamic response and steady-state efficiency provided valuable insights for enhancing MPPT controller performance. [ABSTRACT FROM AUTHOR]

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This study uses the Anomaly Transformer model to find anomalies in photovoltaic energy generation in Malang, Indonesia. The main background of this study is the lack of satellite monitoring in this region and the importance of annual data for electricity generation forecasting. Temperature scattered direct solar radiation, and hourly electricity production are all part of the dataset used which is only available since 2019. Anomalies were detected at 05.00 and 16.00 WIB, indicating instability in the energy supply due to high temperatures in the morning and heavy rain in the afternoon. Detection of these anomalies is important to improve the efficiency and reliability of photovoltaic systems, reduce operational costs, and reduce the risk of system failure. Indonesia has many challenges for photovoltaic energy generation due to its unique location, with many islands located close to the equator. The use of the Anomaly Transformer algorithm improves the accuracy of anomaly detection over conventional methods. This algorithm helps to find complex patterns in very large time series. The results show that the anomaly transformer model can effectively detect anomalous patterns. It offers ideas to improve the stability and efficiency of photovoltaic systems in Malang and other areas with comparable environmental conditions. Improved energy efficiency and environmental sustainability are the results of anomaly pattern detection. [ABSTRACT FROM AUTHOR]

This paper proposes a control strategy for grid-following inverter control and grid-forming inverter control developed for a Solar Photovoltaic (PV)–battery-integrated microgrid network. A grid-following (GFL) inverter with real and reactive power control in a solar PV-fed system is developed; it uses a Phase Lock Loop (PLL) to track the phase angle of the voltages at the PCC and adopts a vector control strategy to adjust the active and reactive currents that are injected into the power grid. The drawback of a GFL inverter is that it lacks the capability to operate independently when the utility grid is down due to outages or disturbances. The proposed grid-forming (GFM) inverter control with a virtual synchronous machine provides inertia to the grid, generates a stable grid-like voltage and frequency and enables the integration of the grid. The proposed system incorporates a battery energy storage system (BESS) which has inherent energy storage capability and is independent of geographical areas. The GFM control includes voltage and frequency control, enhanced islanding and black start capability and the maintenance of the stability of the grid-integrated system. The proposed model is validated under varying irradiance conditions, load switching, grid outages and temporary faults with fault ride-through (FRT) capability, and fast frequency response and stability are achieved. The proposed model is validated under varying irradiance conditions, load switching, grid outages and line faults incorporating fault ride-through capability in GFM-based control. The proposed controller was simulated in a 100 MW solar PV system and 60 MW BESS using the MATLAB/Simulink 2023 tool, and the experimental setup was validated in a 1 kW grid-connected system. The percentage improvement of the system frequency and voltage with FRT-capable GFM control is 69.3% and 70%, respectively, and the percentage improvement is only 3% for system frequency and 52% for grid voltage in the case of an FRT-capable GFL controller. The simulation and experimental results prove that GFM-based inverter control achieves fast frequency response, and grid stability is also ensured. [ABSTRACT FROM AUTHOR]

A high penetration of electric vehicles (EVs) will deeply impact the management of electric power systems. The risk of not providing adapted EV pricing signals can lead to inefficient investments in grid infrastructure. To avoid costly grid reinforcements and to ensure proper guidance for EV charging, a solution allowing customers to access EV-only rates without installing a separate meter, which we refer to as submetering, is an attractive option for EV owners and grid operators. We develop a game-theoretical model expressed and treated as a mathematical program with equilibrium constraints (MPEC) to capture the interaction between a national regulatory authority (NRA) designing these tariffs and heterogeneous agents. This framework represents a stylized regulatory setup applicable to several European countries. First, we analyse the conditions in which EV-only tariffs can be applied for domestic charging by comparing different energy profiles. Second, we study the impact of EV charging on different tariff structures to identify the most efficient way of recovering network costs. We found that the adoption of submetering under a pure volumetric tariff can bring yearly gains varying from $ 64 to $ 125 to consumers with EV. Finally, we derive policy implications from the results. [ABSTRACT FROM AUTHOR]

The emergence of semi‐transparent solar panels offers opportunities for their application in greenhouses where the radiation is a critical issue. The light passing through these panels is often affected, leading to a decrease in certain wavelengths that could potentially impact plant growth and quality. To address this concern, this study is performed to investigate the growth and yield of tomato and broccoli plants cultivated under semi‐transparent photovoltaic solar panels compared to those grown under conventional greenhouse plastic. Their physiological and metabolic changes are also examined. A decrease in the yellow/green spectrum after installation of the solar panels is observed. In both plants, slight alterations are observed by solar panels, enhancing even the height of plants and fruit yield in case of tomato. However, both plants showed changes related to their photosynthetic activity and some metabolite concentration. Specifically, there are significant reductions in An (photosynthetic rate) and lower levels of trigonelline in plants grown under solar panels. These reductions may be attributed to the different radiation conditions experienced by the plants, which do not appear to directly impact plant growth. The obtained results highlight the promising potential of solar panel‐integrated greenhouses that optimize economic and energy benefits while maintaining product quality. [ABSTRACT FROM AUTHOR]

The inherent power fluctuations of wind, photovoltaic (PV) and bioenergy with carbon capture and storage (BECCS) create a temporal mismatch between energy supply and demand. This mismatch could lead to a potential resurgence of fossil fuels, offsetting the effects of decarbonization and affecting the realization of the Paris target by limiting global warming to below 2 °C in the 21st century. While application of energy storage is widely recommended to address this limitation, there is a research gap to quantify the impacts of energy storage limitation on global warming. Here, we analyzed the hourly variation of global wind and PV power during the period 1981–2020 and the monthly capacity of biomass production in 2019, and thus quantified the impact of decreasing the capacity of energy storage on global warming using a state-of-the-art Earth system model. We found that global warming by 2100 in the SSP1-2.6 scenario would increase by about 20% and exceed 2 °C without deploying energy storage facilities. Achieving the 2 °C target requires reducing power losses of wind and PV by at least 30% through energy storage. This requirement delivers to a cumulative storage capacity of 16.46 TWh using batteries during the period 2021–2100, leading to the international trade of cobalt and manganese across countries due to deficits of minerals at a country level. In the context of energy security, we highlight the importance of considering the limitations of energy storage and mineral shortage in the forthcoming policies of decarbonization. [ABSTRACT FROM AUTHOR]

This study addresses the pivotal challenge of transitioning from nuclear to renewable energy sources, considering the distinctive energy landscape of South Korea characterized by high land costs and high dependence on nuclear energy. Amidst global momentum toward sustainable and carbon-neutral energy, South Korea's Renewable Energy 3020 Implementation Plan aims to achieve 20% of power generation from renewables by 2030. Shifting away from nuclear energy, however, may lead to rising energy costs, supply disruptions, and environmental ramifications. Furthermore, achieving grid parity between renewable energy and nuclear power by the late 2030s is unlikely, in contrast to earlier projections. This is primarily due to the comparatively lower production cost of nuclear energy. To expedite the shift toward renewable energy, our study suggests transitioning from the Renewable Energy Portfolio Standard (RPS) to a Feed-in-Tariff (FiT) system. This change would offer voluntary incentives for investment in renewable energy. Additionally, we compute Feed-in-Tariff subsidies required to achieve grid parity by 2030, concluding that the amount of subsidies required to reach grid parity by 2030 is 54% of retail electricity price. This research offers valuable insights for policy formulation and energy transition planning. [ABSTRACT FROM AUTHOR]

Our research explores hybrid perovskite solar cells, promising low-cost and high-efficiency photovoltaic solutions. Despite challenges, optimizations like interface engineering enhance performance for future commercial use. Study of different physical parameters with the help of SILVACO and MATLAB Simulink for cell modeling. Long-term stability and cost reductions are among the most significant challenges to broad commercialization Future research will be around trying different parameter values. There searcher said this project represents an important step forward in the development of hybrid perovskite solar cells, which could be a key partof a new wave of clean energy sources that are needed as global consumption levels continue to rise. The solar cells studied herein are detailed by the six-scan structure: Glass/Indium Tin Oxide (ITO) / Electron Transport Layer - (N layer) - Active Layer (Perovskite) - Hole transport_layer (Payer) - Metal Electrode; Glass/ITO/TiO2/Pero_Aardes Spiro-OMeTAD/Au. It delivers the energy conversion efficiency of 19.12% with a fill factor (FF) of 80.53%, an open-circuit voltage at Voc =1.14 Vandshort circuit current density Jsc=20.88 mA/cm²,respectively The active layer is a 0.25 -thick CH3NH3PbI3 perovskite, and the TiO2 layer thickness was set at 0.02

Integrating renewable energy resources into the existing generation capacity can handle the additional load resulting from the EV charging system, even when the majority of the EVs are charged during off-peak hours. This paper comprehensively analyzes EV charging methods with a particular focus on both grid-based direct charging and the utilization of renewable energy sources. However, the most practical approach for EV charging is through large-scale grid-based renewable energy stations. This study outlines the significant challenges facing the application of EV chargers. Overcoming these challenges is vital for the widespread adoption of new technologies such as Wireless power transfer charging systems in the EV sector. Wireless charging technology still faces several issues, such as energy loss during transmission, alignment between the coils, and quick and safe power delivery. One of the significant challenges facing wireless chargers is the need to optimize efficiency while ensuring convenient and reliable charging as outlined in this study. Different wireless charger configurations are presented for stationary EV charging systems by incorporating photovoltaic systems into charging stations and supervisory bases. The application of series-series wireless charger system as an emerging technology for EV chargers is analyzed and simulated as a recommended solution for EV wireless chargers. The system overall efficiency is approximately 98%. The charging system can operate reliably by mitigating the effects of load and grid disturbances.

The paper analyzes the application flexibility of partial power converters for interfacing photovoltaic strings in dc microgrids. Step-up/down partial power converters were considered for providing the lowest active power processing. This study considers three Si-based photovoltaic modules commonly used in residential applications: 54-, 60-, and 66-cell. Different configurations of photovoltaic strings are analyzed to find at what voltages most energy is generated in hot and cold climates. Combining these results with the operating voltage range of a droop-controlled dc microgrid yields design requirements for the partial power interface converters. The proposed design limits the maximum power the converter processes to optimize its components. Next, the application of the topology morphing control is studied regarding the performance enhancement of partial power converters. Experimental results verify good converter performance and feasibility of efficiency improvement with the topology morphing control.

Photovoltaic (PV) water pumping systems address water accessibility challenges in isolated regions by offering sustainable, self-sufficient solutions that do not rely on the power grid. These systems provide enduring advantages, such as reduced operational expenses, while also making a substantial contribution to agricultural progress and enhancing the quality of life in rural areas. The utilization of solar energy for powering rural areas has been significantly reduced due to recent technological breakthroughs. The objective of this study was to utilize MATLAB-Simulink models to simulate a photovoltaic water pumping system and generate an ideal direct current (DC) voltage at the input of the inverter. In addition, the machine side utilizes space vector modulation (DTC-SVM), while the DC voltage side employs fuzzy logic control (FLC). The fuzzy logic methodology is highly effective in dealing with non-linear and complicated systems, providing strong control in situations where conventional methods may face difficulties. DTC-SVM improves the management of motors by providing superior dynamic performance, minimizing torque fluctuations, and increasing overall efficiency. This makes it a highly valuable technique for motor control systems. When the DTC-SVM method is applied to the induction motor instead of the field-oriented control (FOC) and conventional direct torque control (DTC), it was discovered that the centrifugal pump exhibits a more rapid dynamic reaction and performs more effectively. [ABSTRACT FROM AUTHOR]

The use of the technology roadmap has become a key tool for forecasting future market directions and technological developments, and it is a basis for making strategic decisions. The literature highlights its usefulness, especially in key technological areas, to guide and prioritize company investments in Research & Development (R&D). Our work is based on the application of this approach to a key technological area, one that is prioritized at the country level - renewable energies. The research focused on data from the case study of a company in the hotel sector located in a city in the Colombian Caribbean region. The development of the study facilitated the definition of technological objectives, the selection of strategic alternatives and the planning of innovation actions in a company in the hotel sector that seeks to incorporate photovoltaic energy as part of its sustainability strategy. [ABSTRACT FROM AUTHOR]

The research study provides a techno-economic analysis for the green hydrogen generation based solar radiation data for both the single and hybrid alkaline water electrolyzer and energy storage system systems. In addition, a carbon footprint study is conducted to estimate the developed system carbon dioxide emissions. The optimal size of the alkaline water electrolyzer and energy storage system is determined by a genetic algorithm that takes into account a carbon tax on carbon emissions. Based on itemized cost estimating findings, unit hydrogen production costs for a single system and a hybrid system were $6.88/kg and $8.32/kg respectively. Furthermore, capital cost it has been found as a key element in determining the optimal scale of the alkaline water electrolyzer and energy storage system, which are essential for minimizing the unit hydrogen production cost. Lastly, an effort to minimize the capital cost of producing green hydrogen is required when the rising trend of the carbon dioxide tax is taken into account. [ABSTRACT FROM AUTHOR]

Introduction: A radical shift in energy production is underway worldwide, replacing fossil fuels with renewable sources and causing structural changes in power generation systems. Problem statement: Photovoltaic installations for self-consumption have experienced a steep increase in recent years. They have reached a significant installed capacity to cause a noticeable reduction in consumption from the national grid, which can cause serious management problems. Objectives: In this work, the evolution of the Spanish demand in the last years is analyzed to identify the influence of self-consumption in the overall demand. In addition, a mathematical model is defined to estimate this influence. Methodology: The demand curves of equivalent days in years with high and low installed self-consumption photovoltaic systems have been compared. Then, an estimation of the electricity generated with this source is proposed, with a mathematical model that takes into account data on solar radiation, installed photovoltaic power for self-consumption and other relevant factors. Results: The analysis of the demand has shown a significant reduction of the electricity demand in daylight hours when the number of self-consumption photovoltaic systems increases. Moreover, the proposed model has been able to provide an estimation of the electricity generated with this source. The addition of these estimates to the actual consumption curves of years with a high number of self-consumption installations gives profiles close to those obtained when self-consumption was low. Recommendation: New storage systems need to be implemented and grid management need to be improved to take advantage of the surpluses produced by photovoltaic systems.

The emergence of semi‐transparent solar panels offers opportunities for their application in greenhouses where the radiation is a critical issue. The light passing through these panels is often affected, leading to a decrease in certain wavelengths that could potentially impact plant growth and quality. To address this concern, this study is performed to investigate the growth and yield of tomato and broccoli plants cultivated under semi‐transparent photovoltaic solar panels compared to those grown under conventional greenhouse plastic. Their physiological and metabolic changes are also examined. A decrease in the yellow/green spectrum after installation of the solar panels is observed. In both plants, slight alterations are observed by solar panels, enhancing even the height of plants and fruit yield in case of tomato. However, both plants showed changes related to their photosynthetic activity and some metabolite concentration. Specifically, there are significant reductions in An (photosynthetic rate) and lower levels of trigonelline in plants grown under solar panels. These reductions may be attributed to the different radiation conditions experienced by the plants, which do not appear to directly impact plant growth. The obtained results highlight the promising potential of solar panel‐integrated greenhouses that optimize economic and energy benefits while maintaining product quality.

In the field of renewable energies, the logistical intricacies of production, as well as the use and storage of photovoltaic energy, have become critical issues. In addition to sheer quantity, the stability of this type of energy is a crucial factor in ensuring the reliability and consistency of power generation. This paper defines Solar Irradiance Stability Factors (SISFs) as indicators complementing electricity production. When planning solar energy production in each geographical area, both the quantity and stability of solar irradiance are necessary for exploitation and determining the quality of solar irradiance. While the average production of solar energy per unit area in each time interval is a widely used parameter in daily practice, the observation of the amplitude of solar irradiance and its influence on energy production in the observed time interval is currently still rare. The SISFs defined in this article are new metrics that mainly depend on the meteorological variability in an area, and the observed time intervals should be in the range of seconds, minutes, or even hours. Larger time intervals are not helpful for the stability of solar irradiance in energy production and logistics from the source to the destination. They provide a complementary and more accurate measure of how suitable a particular geographical area is for producing solar energy.

The significant expansion of renewable energies has led to an increased importance of storage systems. Decentralized storage solutions, including Home Battery Energy Storage Systems (HBESSs) and District Battery Energy Storage Systems (DBESSs), play a crucial role in this context. This study compares individual HBESSs with a community-used DBESS regarding the grade of autarky and self-consumption, specifically focusing on a planned residential area consisting of 36 single-family houses. A simulation tool was developed to conduct load flow simulations based on household electricity consumption, wallbox profiles for electric vehicle charging, and photovoltaic generation data across various battery capacities and system boundaries. The results demonstrate that the DBESS, compared to individual HBESSs with equivalent cumulative battery capacities, can achieve a maximum increase in the grade of autarky of up to 11.6%, alongside an 8.0% increase in the grade of self-consumption for the given use case. In terms of capacity, the DBESS allows for a saving of up to 68% compared to HBESS to achieve similar results for the studied neighborhood.

The global photovoltaic (PV) installed capacity, vital for the electric sector’s decarbonation, reached 1552.3 GWp in 2023. In France, the capacity stood at 19.9 GWp in April 2024. The growth of the PV installed capacity over a year was nearly 32% worldwide and 15.7% in France. However, integrating PV electricity into grids is hindered by poor knowledge of rooftop PV systems, constituting 20% of France’s installed capacity, and the lack of measurements of the production stemming from these systems. This problem of lack of measurements of the rooftop PV power production is referred to as the lack of observability. Using ground-truth measurements of individual PV systems, available at an unprecedented temporal and spatial scale, we show that by estimating the PV power production of an individual rooftop system by combining solar irradiance and temperature data, the characteristics of the PV system inferred from remote sensing methods and an irradiation-to-electric power conversion model provides accurate estimations of the PV power production. We report an average estimation error (measured with the pRMSE) of 10% relative to the system size. Our study shows that we can improve rooftop PV observability, and thus its integration into the electric grid, using little information on these systems, a simple model of the PV system, and weather data. More broadly, this study shows that limited information is sufficient to derive a reasonably good estimation of the PV power production of small-scale systems.

More than two-thirds of the installed solar power in Brazil comes from distributed mini-generation and microgeneration (DMMG), mostly residential and for local self-consumption of solar PV. DMMG had its legal framework approved in 2022, gradually introduces charges for distribution network use, previously exempt. To understand these implications, this article compiles recent legislative and normative changes, particularly for solar PV DMMG projects. In addition, the present study focuses on the use of DMMG systems in the city of Fortaleza in the Northeast Region. The study includes an analysis of the integration of photovoltaic plants in homes in Fortaleza and their economic viability under the new conditions established after 2020. Two residential photovoltaic systems, with varying power levels common in the residential sector of Fortaleza, were studied. Each plant underwent three analyses: one with vested rights; another with 100% taxation of FIO Bl and a third for the current scenario, factoring in the growing FIO B charge from 15% in 2023 to 100% in 2029. Customers who obtained the system by cash payment or financing were considered. An economic feasibility study factored in a 5.79% yearly inflation rate and an 11.35% annual tariff readjustment across the two plants, including sensitivity analysis for this variable.

Rural farms constitute a vital component of a country's agricultural landscape, traditionally reliant on energy installations known for their reliability yet notorious for their energy-intensive and inefficient characteristics. While the smart farm concept, integrating renewable energy sources and resource management technologies, has seen widespread adoption in domestic and industrial sectors, rural farms have been slower to embrace these innovations. This study presents a groundbreaking solution, deployed on a rural farm in Portugal, resulting in an impressive 83.24% reduction in energy consumption sourced from the grid. Notably, this achievement translates to a substantial reduction in CO2 emissions, aligning with the growing need for environmentally sustainable farming practices. The technical intricacies of this pioneering solution are comprehensively described and juxtaposed with other scientific case studies, offering valuable insights for replication. This initiative represents a vital first step towards the integration or combination of conventional farming with photovoltaic energy production, exemplified by agrivoltaic systems. In conclusion, this research showcases the potential for rural farms to significantly enhance energy efficiency and financial viability, thereby contributing to a more sustainable and cost-effective agricultural sector. These findings serve as a model for similar endeavors, paving the way for a greener and more economically viable future for rural farming practices. [ABSTRACT FROM AUTHOR]

Batteries are widely used for energy storage in stand-alone PV systems. However, both PV modules and batteries exhibit nonlinear behavior. Therefore, battery modeling is an essential step toward appropriate battery control and overall PV system management. Empirical models remain reliable for lead-acid batteries, especially the Copetti model, which describes many inner and outer battery phenomena, including temperature dependency. However, the parameters of the Copetti model require further adjustment to increase its ability to accurately represent battery behavior. Recently, metaheuristic algorithms have been employed for parameter identification, especially hybrid algorithms that combine the advantages of two or more algorithms. This paper proposes an enhanced battery model based on the Copetti model. The parameter identification of the enhanced model has been carried out using a novel hybrid PSO-GA algorithm (HPGA). The hybrid algorithm combines GA and PSO in a cascade configuration, with GA as the master algorithm. The HPGA algorithm has been compared with other algorithms, namely GA, PSO, ABC, COA, and a hybrid GWO-COA, to reveal its advantages and disadvantages. The NRMSE is used to evaluate algorithms in terms of tracking speed and efficiency. HPGA shows an improvement in tracking efficiency compared to GA and PSO. The proposed model is validated on several charging-discharging data and exhibits a 15% lower mean error compared to the Copetti model with original parameters. Additionally, the proposed model demonstrates a lower mean error of 0.16% compared to other models in the literature with a 0.36% mean error at least. [ABSTRACT FROM AUTHOR]

This paper proposes a novel short-term photovoltaic voltage (PV) prediction scheme using IoT sensor data with the two-stage neural network model. It is efficient to use environmental data provided by the meteorological agency to predict future PV generation. However, such environmental data represent the average value of the wide area, and there is a limitation in detecting environmental changes in the specific area where the solar panel is installed. In order to solve such issues, it is essential to establish IoT sensor data to detect environmental changes in the specific area. However, most conventional research focuses only on the efficiency of IoT sensor data without taking into account the timing of data acquisition from the sensors. In real-world scenarios, IoT sensor data is not available precisely when needed for predictions. Therefore, it is necessary to predict the IoT data first and then use it to forecast PV generation. In this paper, we propose a two-stage model to achieve high-accuracy prediction results. In the first stage, we use predicted environmental data to access IoT sensor data in the desired future time point. In the second stage, the predicted IoT sensors and environmental data are used to predict PV generation. Here, we determine the appropriate prediction scheme at each stage by analyzing the model characteristics to increase prediction accuracy. In addition, we show that the proposed prediction scheme could increase prediction accuracy by more than 12% compared to the baseline scheme that only uses a meteorological agency to predict PV generation. [ABSTRACT FROM AUTHOR]

The recent developments in the design, planning, and operation of distribution systems indicate the need for a modern integrated infrastructure in which participants are managed through the perceptions of a utility company in an economic network (e.g., energy loss reduction, restoration, etc.). The penetration of distributed generation units in power systems are growing due to their significant influence on the key attributes of power systems. As a result, the placement, type, and size of distributed generations have an essential role in reducing power loss and lowering costs. Power loss minimization, investment and cost reduction, and voltage profile improvement combine to form a conceivable goal function for distributed generation allocation in a constrained optimization problem, and they require a complex procedure to control them in the most appropriate way while satisfying network constraints. Such a complex decision-making procedure can be solved by adjusting the dynamic optimal power flow problem to the associated network. The purpose of the present work is to handle the distributed generation allocation problem for photovoltaic units, attempting to reduce energy and investment costs while accounting for generation unpredictability as well as load fluctuation. The problem is analyzed under various scenarios of solar radiation through a stochastic programming technique because of the intense uncertainty of solar energy resources. The formulation of photovoltaic distributed generation allocation is represented as a mixed-integer second-order conic programming problem. The IEEE 33-bus and real-world 136-bus distribution systems are tested. The findings illustrate the efficacy of the proposed mathematical model and the role of appropriate distributed generation allocation. [ABSTRACT FROM AUTHOR]

The presence of shadows is one of the main disadvantages of photovoltaic solar panel installations in urban environments. This article analyses their effect on solar installations performed on urban elements where the use of solar energy can be considered novel: bus shelters. For this purpose, the PVGIS tool is used in combination with a new methodology for the extraction of the shadow horizon profile from LiDAR point clouds. The results show a 29.90% and 37% reduction of calculated solar radiation using horizon profiles derived from LiDAR point clouds of 0.5 pts/m2 and 1 pt/m2, respectively, versus no horizon profile. By taking shading into account, thanks to this study it is possible to make a more realistic prediction of the use of the electrical energy generated by the sun to cover urban energy consumption in bus shelters. Results show that the energy surplus produced overall allows these elements to be converted into charging points for light electric vehicles, allowing up to 35 units per day/bus shelter to be charged. The use of bus shelters as a place to generate clean energy through solar energy and charge light vehicles makes it possible to move towards sustainable and environmentally friendly cities. [ABSTRACT FROM AUTHOR]

The electrolysis of renewable energy to produce hydrogen has become a strategy for supporting a decarbonized economy. However, it is typically not cost-effective compared to conventional carbon-emitting methods. Due to the predicted intermediate of low-and zero-marginal-cost renewable energy sources, the ability of electrolysis to connect with electricity pricing offers a novel way to cost reduction. Moreover, renewables, particularly photovoltaics, have a deflationary effect on the value of the grid when they are deployed. This study investigates solar electrolysis configurations employing photovoltaic cells to feed a proton exchange membrane water electrolyzer for hydrogen production. Using experimental meteorological data at 1-min precision, the system has been evaluated in Baghdad, the capital of Iraq. Positioned at the yearly optimum tilt angle for the selected site, the solar array is rated at 12 kWp. Temperature effects on solar module energy loss are taken into account. Several electrolyzers with capacities ranging from 2 to 14 kW in terms of hydrogen production were examined to determine the efficacy and efficiency of renewable sources. MATLAB was utilized for the simulation procedure, with a 2021–2035 project lifespan in mind. The results suggest that a variety of potentially cost-competitive options exist for systems with market configurations that closely approximate wholesale renewable hydrogen. At 4313 h of operation per year, the planned photovoltaic array generated 18,892 kWh of energy. The achieved hydrogen production cost ranges between $5.39/kg and $3.23/kg, with an ideal electrolyzer capacity of 8 kW matching a 12 kWp photovoltaic array capable of producing 450 kg/year of hydrogen at a cost of $3.23/kg. [ABSTRACT FROM AUTHOR]

This research established the technoeconomic feasibility of an on-grid hybrid renewable energy system for delivering electricity to the deanery building of the Engineering College at the University of Diyala, Iraq. The most cost-effective system design was discovered by modeling and optimization, with an average daily load of 25.0 kWh and total cost and energy cost of $5142 and $0.05/kWh, respectively. In relation to the energy generated by conventional resources, the designed system is more cost-effective and has a lower carbon footprint of about 13,052 kg/year of CO2 emissions avoided. According to the research, using a hybrid power system to electrify and decarbonize the electrical energy supply could be a reliable and economical way to do both at the same time. Innovation is in integrating the suggested hybrid system so that the use of electricity can effectively be decreased to meet the load. As a result, the system components are not oversized, which reduces system costs and reduces emissions. [ABSTRACT FROM AUTHOR]

The conservation of the environment and the use of clean energy is one of the main concerns of international governments. In this sense, encouraging the use of clean energy, both locally, nationally, and internationally, contributes to the development of countries. In this order of ideas, this work was motivated with the purpose of contributing to the scope of the SDGs at the national level, specifically, in the city of Barranquilla (Colombia). The thermal sensation inside the public transport in Barranquilla limits the quality of the service and, consequently, the satisfaction of the users due to the high temperatures (T > 30 °C). To address this problem, it is necessary to implement air conditioning systems that improve comfort conditions and are friendly to the environment. In this study, the feasibility of implementing photovoltaic panels as an alternative energy source for air conditioning units in public transport was examined. The study began with the dimensioning of the photovoltaic system and the accumulation of energy. A stress analysis was then performed on the chassis and bodywork of a selected bus. Finally, the work was evaluated based on the results obtained from the dimensioning of the mentioned systems. The results confirmed that a photovoltaic generator with a power of 35.88 kW and an energy storage capacity of 481,204 Ah is required. Additionally, the results also confirmed that the chassis and bodywork are structurally sound. The economic analysis carried out confirmed a Net Present Value and an Internal Rate of Return of 22,936 USD and 11.05%, respectively. The energy alternative proposed for the transport sector, based on the application of photovoltaic energy, constitutes an advance to meet international objectives in relation to the use of clean energy. [ABSTRACT FROM AUTHOR]